Bibliographic record
Abstract
Since 1945 the South China Sea and the western Pacific has functioned as an uncontested global common patrolled by overwhelming U.S. naval and air power projected from a series of peripheral and over the horizon bases. The dramatic rise of China alters this situation and has transformed the South China Sea into a frontier of control as China seeks to morph this maritime theater into a landward extension of the Chinese coast where it can deploy land-based tactics into an arena previously dominated by maritime power and tactics to secure the South China Sea as a de facto territorial water that serves multiple Chinese strategic interests. Hence, the attempt by a land-based Eurasian power (China) to carve a permanent bridgehead into Spykman’s Eurasian maritime periphery. Against, this trend the United States has countered with President Obama’s Asian Pivot. However, the implementation of the Asian Pivot is limited by several post Cold War developments and certain constraints inherent in the geographic setting of the South China Sea. Beyond the South China Sea, the geographic setting favors the U.S. and its allies. Consequently, American options acting singly or in coalition with other nations, most notably Japan and Australia, remain more flexible and able to serve as a long term counterweight to Chinese force projection capabilities into the western Pacific proper.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.020 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".